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Record W7098383830

0730-7268/05 $12.00 �.00 Environmental Toxicology EFFECTS OF WATER HARDNESS ON TOXICOLOGICAL RESPONSES TO CHRONIC WATERBORNE SILVER EXPOSURE IN EARLY LIFE STAGES OF RAINBOW TROUT (ONCORHYNCHUS MYKISS)

2004· article· en· W7098383830 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRainbow troutHard waterTroutWater qualitySoft waterToxicity
DOInot available

Abstract

fetched live from OpenAlex

Abstract—Rainbow trout embryos and larvae were exposed to 0, 0.1, and 1 �g/L total silver (as AgNO 3) in water of three different hardnesses (soft water [2 mg/L as CaCO 3], moderately hard water [150 mg/L], and hard water [400 mg/L]) in a flowthrough system from fertilization to swim-up (64 d). The objective of the study was to investigate the effects of water hardness on chronic silver toxicity. In the absence of silver, elevating hardness had a positive effect on early life stage survival and development, significantly decreasing mortality and accelerating time to 50 % swim-up. Following hatch, exposure to 1 �g/L Ag significantly increased mortality relative to exposure to 0 �g/L Ag. No significant effects of silver on time to 50 % hatch were observed; however, time to 50 % swim-up was delayed, and 50 % swim-up was not achieved over the course of the experiment during some exposures to 1 �g/L Ag. These results suggest that the current Canadian Water Quality Guideline

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.4950.187

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.209
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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